SQL Function Reference¶

Complete reference for all Onager SQL functions.

Parameters shown inside square brackets are optional named parameters with defaults, passed as name := value. Functions whose signature includes [, directed] accept a directed boolean named parameter. The default is false for every function, which treats the input edge list as undirected.

Graph Management Functions¶

Function	Returns	Description
`onager_create_graph(name, directed)`	`integer`	Create a named graph (0=success)
`onager_drop_graph(name)`	`integer`	Delete a named graph
`onager_add_node(graph, node_id)`	`integer`	Add a node to graph
`onager_add_edge(graph, src, dst, weight)`	`integer`	Add a weighted edge
`onager_list_graphs()`	`varchar`	List all graphs (JSON array)
`onager_node_count(graph)`	`bigint`	Count nodes in graph
`onager_edge_count(graph)`	`bigint`	Count edges in graph

Scalar Query Functions¶

Function	Returns	Description
`onager_node_in_degree(graph, node)`	`bigint`	In-degree of a node
`onager_node_out_degree(graph, node)`	`bigint`	Out-degree of a node

Centrality Functions¶

Function	Returns	Description
`onager_ctr_pagerank(edges [+ weights] [, damping, iterations, tolerance, directed])`	`node_id, rank`	PageRank centrality
`onager_ctr_degree(edges [, directed])`	`node_id, in_degree, out_degree`	Degree centrality
`onager_ctr_betweenness(edges [, normalized, directed])`	`node_id, betweenness`	Betweenness centrality
`onager_ctr_closeness(edges [, directed])`	`node_id, closeness`	Closeness centrality
`onager_ctr_eigenvector(edges [, max_iter, tolerance, directed])`	`node_id, eigenvector`	Eigenvector centrality
`onager_ctr_katz(edges [, alpha, beta, max_iter, tolerance, directed])`	`node_id, katz`	Katz centrality
`onager_ctr_harmonic(edges [, directed])`	`node_id, harmonic`	Harmonic centrality
`onager_ctr_personalized_pagerank(edges [, damping, max_iter, tolerance, directed])`	`node_id, score`	Personalized PageRank
`onager_ctr_voterank(edges [, num_seeds, directed])`	`node_id`	VoteRank influential spreaders
`onager_ctr_local_reaching(edges [, distance, directed])`	`node_id, centrality`	Local reaching centrality
`onager_ctr_laplacian(edges [, directed])`	`node_id, centrality`	Laplacian centrality

Community Detection Functions¶

Function	Returns	Description
`onager_cmm_louvain(edges [, seed])`	`node_id, community`	Louvain modularity optimization
`onager_cmm_components(edges)`	`node_id, component`	Connected components
`onager_cmm_label_prop(edges [, max_iter, seed])`	`node_id, label`	Label propagation
`onager_cmm_girvan_newman(edges [, communities])`	`node_id, community`	Girvan-Newman edge betweenness
`onager_cmm_spectral(edges [, k, seed])`	`node_id, community`	Spectral clustering
`onager_cmm_infomap(edges [, max_iter, seed])`	`node_id, community`	Infomap community detection

Link Prediction Functions¶

Function	Returns	Description
`onager_lnk_jaccard(edges)`	`node1, node2, coefficient`	Jaccard coefficient
`onager_lnk_adamic_adar(edges)`	`node1, node2, score`	Adamic-Adar index
`onager_lnk_pref_attach(edges)`	`node1, node2, score`	Preferential attachment
`onager_lnk_resource_alloc(edges)`	`node1, node2, score`	Resource allocation
`onager_lnk_common_neighbors(edges)`	`node1, node2, count`	Common neighbors count

Metric Functions¶

Function	Returns	Description
`onager_mtr_diameter(edges [, directed])`	`diameter`	Graph diameter
`onager_mtr_radius(edges [, directed])`	`radius`	Graph radius
`onager_mtr_avg_clustering(edges)`	`avg_clustering`	Average clustering coefficient
`onager_mtr_avg_path_length(edges [, directed])`	`avg_path_length`	Average shortest path length
`onager_mtr_transitivity(edges)`	`transitivity`	Global clustering (transitivity)
`onager_mtr_triangles(edges)`	`node_id, triangles`	Triangle count per node
`onager_mtr_assortativity(edges [, directed])`	`assortativity`	Degree assortativity coefficient
`onager_mtr_density(edges [, directed])`	`density`	Graph density (0 to 1)

Path and Traversal Functions¶

Function	Returns	Description
`onager_pth_dijkstra(edges [+ weights] [, source, directed])`	`node_id, distance`	Shortest paths from source
`onager_pth_bellman_ford(weighted_edges [, source, directed])`	`node_id, distance`	Shortest paths (negative weights)
`onager_pth_floyd_warshall(weighted_edges [, directed])`	`src, dst, distance`	All-pairs shortest paths
`onager_trv_bfs(edges [, source, directed])`	`node_id`	Breadth-first traversal
`onager_trv_dfs(edges [, source, directed])`	`node_id`	Depth-first traversal

Approximation Functions¶

Function	Returns	Description
`onager_apx_max_clique(edges)`	`node_id`	Maximum clique (approximation)
`onager_apx_independent_set(edges)`	`node_id`	Maximum independent set (approx)
`onager_apx_vertex_cover(edges)`	`node_id`	Minimum vertex cover (approx)
`onager_apx_tsp(weighted_edges [, start])`	`order, node_id`	TSP tour (greedy approx)

Minimum Spanning Tree¶

Function	Returns	Description
`onager_mst_kruskal(weighted_edges)`	`src, dst, weight`	Kruskal's MST
`onager_mst_prim(weighted_edges)`	`src, dst, weight`	Prim's MST

Generator Functions¶

Function	Returns	Description
`onager_gen_erdos_renyi(n, p [, seed])`	`src, dst`	Random graph (G(n,p))
`onager_gen_barabasi_albert(n, m [, seed])`	`src, dst`	Scale-free graph
`onager_gen_watts_strogatz(n, k, beta [, seed])`	`src, dst`	Small-world graph

Subgraph Operations¶

Function	Returns	Description
`onager_sub_ego_graph(edges [, center, radius])`	`src, dst`	Ego graph around a node
`onager_sub_k_hop(edges [, start, k])`	`node_id`	Nodes within k hops
`onager_sub_induced(edges_with_filter)`	`src, dst`	Induced subgraph

Parallel Algorithms¶

Function	Returns	Description
`onager_par_pagerank(edges [+ weights] [, damping, iterations, tolerance, directed])`	`node_id, rank`	Parallel PageRank
`onager_par_bfs(edges [, source or sources, directed])`	`[source,] node_id`	Parallel BFS traversal
`onager_par_shortest_paths(edges [, source or sources, directed])`	`[source,] node_id, distance`	Parallel shortest paths
`onager_par_components(edges)`	`node_id, component`	Parallel connected components
`onager_par_clustering(edges)`	`node_id, coefficient`	Parallel clustering coefficients
`onager_par_triangles(edges)`	`node_id, triangles`	Parallel triangle count

Utility Functions¶

Function	Returns	Description
`onager_version()`	`varchar`	Extension version
`onager_last_error()`	`varchar`	Last error message

onager_last_error() is best-effort: the error state is thread-local, and DuckDB may run the failing call and the onager_last_error() call on different worker threads, so the result can be NULL or stale. A failed query surfaces its message directly through the SQL error, which is the reliable channel.

See Input Formats for details on how to pass graph data to functions.